GeoViSTA learns unified geospatial embeddings from co-registered imagery and tabular data via bilateral cross-attention and joint masked autoencoding, yielding better linear probing performance on mortality and fire hazard prediction tasks.
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications
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GeoViSTA: Geospatial Vision-Tabular Transformer for Multimodal Environment Representation
GeoViSTA learns unified geospatial embeddings from co-registered imagery and tabular data via bilateral cross-attention and joint masked autoencoding, yielding better linear probing performance on mortality and fire hazard prediction tasks.